• Journal of Radiation Industry
• /
• v.17 no.4
• /
• pp.551-557
• /
• 2023

In recent years, radiation has become a socially important issue, increasing the need for accurate prediction of radiation levels. In this study, machine learning-based models such as Multiple Linear Regression (MLR), Random Forest (RF), XGBoost, and LightGBM, which predict the dose rate by time(nSv h^-1) by selecting only important variables, were used, and the correlation between temperature, humidity, cumulative precipitation, wind direction, wind speed, local air pressure, sea pressure, solar radiation, and radiation dose rate (nSv h^-1) was analyzed by collecting weather data and radiation dose rate for about 6 months in Jangseong, Jeollanam-do. As a result of the evaluation based on the RMSE (Root Mean Squared Error) and R-Squared (R-Squared coefficient of determination) scores, the RMSE of the XGBoost model was 22.92 and the R-Squared was 0.73, showing the best performance among the models used. As a result of optimizing hyperparameters of all models using the GridSearch method and comparing them by adding variables inside the measuring instrument, it was confirmed that the performance improved to 2.39 for RMSE and 0.99 for R-Squared in both XGBoost and LightGBM.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.6C
• /
• pp.384-390
• /
• 2011

The paper derives formulas for the mean-squared error distortion and resulting signal-to-noise (SNR) ratio of a fixed-rate scalar quantizer designed optimally in the minimum mean-squared error sense for a Gaussian density with the standard deviation ${\sigma}_q$ when it is mismatched to a Laplacian density with the standard deviation ${\sigma}_q$. The SNR formulas, based on the key parameter and Bennett's integral, are found accurate for a wide range of $p\({\equiv}\frac{\sigma_p}{\sigma_q}\){\geqq}0.25$. Also an upper bound to the SNR is derived, which becomes tighter with increasing rate R and indicates that the SNR behaves asymptotically as $\frac{20\sqrt{3{\ln}2}}{{\rho}{\ln}10}\;{\sqrt{R}}$ dB.

• International journal of advanced smart convergence
• /
• v.13 no.1
• /
• pp.206-211
• /
• 2024

This study used a total of 205,565 datasets of 'voltage', 'current', '℃', and 'time(s)' to systematically analyze the properties and performance of solid electrolytes. As a method for characterizing solid electrolytes, a linear regression model, one of the machine learning models, is used to visualize the relationship between 'voltage' and 'current' and calculate the regression coefficient, mean squared error (MSE), and coefficient of determination (R^2). The regression coefficient between 'Voltage' and 'Current' in the results of the linear regression model is about 1.89, indicating that 'Voltage' has a positive effect on 'Current', and it is expected that the current will increase by about 1.89 times as the voltage increases. MSE found that the mean squared error between the model's predicted and actual values was about 0.3, with smaller values closer to the model's predictions to the actual values. The coefficient of determination (R^2) is about 0.25, which can be interpreted as explaining 25% of the data.

• Korean Journal of Applied Biomechanics
• /
• v.26 no.1
• /
• pp.1-9
• /
• 2016

Objective: The aim of this study is to investigate the association between dance experience and smoothness of hand trajectory during dance by using three jerk-based quantitative methods (integrated squared jerk, mean squared jerk, and dimensionless jerk). Methods: Eleven Korean traditional dancers whose experience of dancing ranged from 5 years to 20 years participated in this study. Dancers performed the Taeguksun motion in Korea traditional dance. Six infrared cameras were used to capture the movement of the hands of the dancers. The smoothness of hand movement was calculated using three jerk-based methods. Results: With regard to the smoothness of the right hand, dance experience was significantly correlated with dimensionless jerk (r=0.656, p=0.028), while dance experience was not significantly correlated with integrated squared jerk (r=0.581, p=0.552) and mean squared jerk. With regard to the smoothness of the left hand, there was no correlation between dance experience and any of the three jerk values. Conclusion: Our results showed that individuals with more dance experience performed the task more smoothly. This study suggests that dimensionless jerk should be used as a predictor for smoothness in dance movement. Thus, our results support the idea that smoothness is an aspect of movement quantity distinct from speed and distance.

• Journal of The Korean Society of Integrative Medicine
• /
• v.5 no.3
• /
• pp.91-99
• /
• 2017

Purpose: The purpose of this study was to examine the relationship among self-efficacy, career attitude maturity, and campus life satisfaction in nursing college students. Method: A total of 277 students agreed to participate in this study from 1 May 2016 to 31 May 2016. Data analysis included t-test, ANOVA, Scheffe's test, and multiple regression using the SPSS/WIN 18.0 program. Results: The results of the analysis revealed a positive correlation between campus life satisfaction and career attitude maturity (r=.316, p=.001); between campus life satisfaction and self-efficacy (r=.256, p=.001); and between self-efficacy and career attitude maturity (r=.469, p=.001). Career attitude maturity had the highest R-squared value of 10% (${\beta}=.22$) for campus life satisfaction, while peer relationships had an R-squared value of 2% (${\beta}=-.18$), residence type of 2% (${\beta}=.14$), and self-efficacy of 1% (${\beta}=.14$), for a total R-squared value of 15%. Discussion: Given these results, individual counseling is recommended to improve campus life satisfaction by helping college students to acquire the skills to foster good interpersonal relationships, self-efficacy, and a positive view of their future vocation. Furthermore, it is essential for an educational environment to support students to ensure that after graduation they become fully-fledged members of society with a sense of pride in their profession.

• The Journal of the Society of Korean Medicine Diagnostics
• /
• v.12 no.1
• /
• pp.42-62
• /
• 2008

Objectives: It is well known that some parameters of the photoplethysmogram (PPG) acquired by time domain contour analysis can be used as markers of vascular aging. But the previous studies that have been performed for frequency domain analysis of the PPG to date have provided only restrictive and fragmentary information. The aim of the present investigation was to determine whether the harmonics extracted from the PPG using a fast Fourier transformation could be used as an index of vascular aging. Methods: The PPG was measured in 600 recruited subjects for 30 second durations, To grasp the gross age-related change of the PPG waveform, we grouped subjects according to gender and age and averaged the PPG signal of one pulse cycle. To calculate the conventional indices of vascular aging, we selected the 5-6 cycles of pulse that the baseline was relatively stable and then acquired the coordinates of the inflection points. For the frequency domain analysis we performed a power spectral analysis on the PPG signals for 30 seconds using a fast Fourier transformation and dissociated the harmonic components from the PPG signals. Results: A final number of 390 subjects (174 males and 216 females) were included in the statistical analysis. The normalized power of the harmonics decreased with age and on a logarithmic scale reduction of the normalized power in the third (r=-0.492, P<0.0001), fourth (r=-0.621, P<0.0001) and fifth harmonic (r=-0.487, P<0.0001) was prominent. From a multiple linear regression analysis, Stiffness index, reflection index and corrected up-stroke time influenced the normalized power of the harmonics on a logarithmic scale. Conclusions: The normalized harmonic power decreased with age in healthy subjects and may be less error prone due to the essential attributes of frequency domain analysis. Therefore, we expect that the normalized harmonic power density can be useful as a vascular aging marker.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.9
• /
• pp.4323-4326
• /
• 2016

Background: The cancer mortality-to-incidence ratio (MIR) has been established as an important measure of health disparities in local and global circumstances. Past work has corroborated a linkage between the colorectal cancer MIR and the World Health Organization (WHO) Health System ranking. The literature further documents many Asian countries having incomplete cancer registries and a lack of comprehensive colorectal cancer screening guidelines. Materials and Methods: The colorectal cancer MIR values for 23 Asian countries were calculated from data obtained from the 2012 GLOBOCAN database. The 2000 World Health Organization (WHO) Health System rankings were used as a proxy for health system infrastructure and responsiveness. A regression equation was calculated with the MIR as the dependent variable and the WHO Health System ranking as the independent variable. Predicted MIR values were next calculated based on the regression results. Actual MIR values that exceeded 0.20 from the predicted MIR were removed as 'divergent' points. The regression equation was then re-plotted. Goodness-of-fit for both regressions was assessed by the R-squared test. Results: Asian countries have a relatively wide colorectal cancer MIR range, from a minimum of 0.24 to a maximum of 0.86. For the full dataset, the adjusted R-squared value for this regression was 0.53. The equation was then used to calculate a predicted MIR, whereby two data points were identified as 'divergent' and removed. The adjusted R-squared for the edited dataset increased to 0.66. Conclusions: Asian countries have a marked range in their colorectal cancer MIR values and there is a strong correlationwith the WHO Health System ranking. These results corroborate the contribution of the MIR as a potentially robust tool in monitoring changes in colorectal cancer care for Asian nations.

• International Commerce and Information Review
• /
• v.11 no.2
• /
• pp.111-126
• /
• 2009

This study analysed determinants of Foreign Direct Investment to ASEAN+ 3 member nations using panel data for which cross-sectional data are combined with time series data. The data for the analysis included the amount of FDI, GDP, and indexes of economic independence. This study collected data from six nations(Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam) whose data were easily available, China and Japan from 2003 to 2007 and analysed them. The results are summarized as follows: Using the pooled OLS method, we found Model 2 had the highest explanatory power whose adjusted R-squared was 89.4%, which accounted for about 89% of foreign investment. Using the fixed effect model, Model 2 had the highest explanatory power whose adjusted R-squared was 96.8%, which accounted for about 97% of foreign investment. Using the probability effect model, Model 5 had the highest explanatory power, but in respect to its statistical significance, only GDP was 1% significant and the rest variables had no significance.

• Journal of the Society of Disaster Information
• /
• v.20 no.1
• /
• pp.82-92
• /
• 2024

Purpose: The purpose of this study is to find a solution to the massive data construction that occurs when fire simulation data is linked to augmented reality and the resulting data overload problem. Method: An experiment was conducted to set the interval between appropriate input data to improve the reliability and computational complexity of Linear Interpolation, a data estimation technology. In addition, a validity verification was conducted to confirm whether Linear Interpolation well reflected the dynamic changes of fire. Result: As a result of application to the underground common area, which is the study target building, it showed high satisfaction in improving the reliability of Interpolation and the operation processing speed of simulation when data was input at intervals of 10 m. In addition, it was verified through evaluation using MAE and R-Squared that the estimation method of fire simulation data using the Interpolation technique had high explanatory power and reliability. Conclusion: This study solved the data overload problem caused by applying digital twin technology to fire simulation through Interpolation techniques, and confirmed that fire information prediction and visualization were of great help in real-time fire prevention.

• International Journal of Computer Science & Network Security
• /
• v.21 no.7
• /
• pp.350-358
• /
• 2021

In modern years, the performance of the students is analysed with lot of difficulties, which is a very important problem in all the academic institutions. The main idea of this paper is to analyze and evaluate the academic performance of the college students with bipolar disorder by applying data mining classification algorithms using Jupiter Notebook, python tool. This tool has been generally used as a decision-making tool in terms of academic performance of the students. The various classifiers could be logistic regression, random forest classifier gini, random forest classifier entropy, decision tree classifier, K-Neighbours classifier, Ada Boost classifier, Extra Tree Classifier, GaussianNB, BernoulliNB are used. The results of such classification model deals with 13 measures like Accuracy, Precision, Recall, F1 Measure, Sensitivity, Specificity, R Squared, Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, TPR, TNR, FPR and FNR. Therefore, conclusion could be reached that the Decision Tree Classifier is better than that of different algorithms.